mlsanityData to 7 Oct 2026

Representing Piecewise Linear Functions by Functions with Small Arity

arXiv 2305.16933 ↗First posted 26 May 2023cs.SC cs.DM cs.LGcited by 7

Not on the map. Why?

Abstract (arXiv)

A piecewise linear function can be described in different forms: as an arbitrarily nested expression of min- and max-functions, as a difference of two convex piecewise linear functions, or as a linear combination of maxima of affine-linear functions. In this paper, we provide two main results: first, we show that for every piecewise linear function there exists a linear combination of max-functions with at most n+1 arguments, and give an algorithm for its computation. Moreover, these arguments are contained in the finite set of affine-linear functions that coincide with the given function in some open set. Second, we prove that the piecewise linear function max(0, x1, ldots, xn) cannot be represented as a linear combination of maxima of less than n+1 affine-linear arguments. This was conjectured by Wang and Sun in 2005 in a paper on representations of piecewise linear functions as linear combination of maxima.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 4 of its 16 references that are in the map. First posted on arXiv 26 May 2023.

Builds on

4 of 16 references.

References · 4

  1. 2016Understanding Deep Neural Networks with Rectified Linear Unitscited by 253
  2. 2021Towards Lower Bounds on the Depth of ReLU Neural Networkscited by 55
  3. 2021Sharp bounds for the number of regions of maxout networks and vertices of Minkowski sumscited by 37
  4. 2021Novel convex decomposition of piecewise affine functionscited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 2; 2026: 2.

7 papers.